A Computational approach to predicting economic regimes in automated exchanges

Wolfgang Ketter, John Collins, Maria L Gini, Alok Gupta, Paul R Schrater

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We present a computational approach to identify dominant market conditions, such as over-supply or scarcity, and to predict market changes in automated exchange environments. Intelligent agents can learn the characteristics of prevailing economic conditions, or regimes, from historical data. Agents can then use real-time observable information to identify the current market regime and forecast upcoming market changes. We show that different market regimes can be effectively identified using our methodology. We also present preliminary work on a method to predict regime transitions. We experimentally validate our approach with data from the Trading Agent Competition for Supply Chain Management.

Original languageEnglish (US)
Title of host publication15th Workshop on Information Technology and Systems, WITS 2005
PublisherUniversity of Arizona
Pages147-152
Number of pages6
StatePublished - Jan 1 2005
Event15th Workshop on Information Technology and Systems, WITS 2005 - Las Vegas, NV, United States
Duration: Dec 10 2005Dec 11 2005

Other

Other15th Workshop on Information Technology and Systems, WITS 2005
CountryUnited States
CityLas Vegas, NV
Period12/10/0512/11/05

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